


'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
					from .tokenization_mbart import MBartTokenizer
else:
					lowerCAmelCase   : Tuple             =				None


lowerCAmelCase   : Dict             =				logging.get_logger(__name__)


lowerCAmelCase   : Tuple             =				{"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

lowerCAmelCase   : Optional[Any]             =				{
    """vocab_file""": {
        """facebook/mbart-large-en-ro""": (
            """https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model"""
        ),
        """facebook/mbart-large-cc25""": (
            """https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model"""
        ),
    },
    """tokenizer_file""": {
        """facebook/mbart-large-en-ro""": """https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json""",
        """facebook/mbart-large-cc25""": """https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json""",
    },
}

lowerCAmelCase   : List[str]             =				{
    """facebook/mbart-large-en-ro""": 1_0_2_4,
    """facebook/mbart-large-cc25""": 1_0_2_4,
}

# fmt: off
lowerCAmelCase   : str             =				["""ar_AR""", """cs_CZ""", """de_DE""", """en_XX""", """es_XX""", """et_EE""", """fi_FI""", """fr_XX""", """gu_IN""", """hi_IN""", """it_IT""", """ja_XX""", """kk_KZ""", """ko_KR""", """lt_LT""", """lv_LV""", """my_MM""", """ne_NP""", """nl_XX""", """ro_RO""", """ru_RU""", """si_LK""", """tr_TR""", """vi_VN""", """zh_CN"""]




class        _UpperCamelCase	(    lowercase__):


				'''simple docstring'''


				_snake_case						       =				VOCAB_FILES_NAMES
				_snake_case						       =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				_snake_case						       =				PRETRAINED_VOCAB_FILES_MAP
				_snake_case						       =				['''input_ids''', '''attention_mask''']
				_snake_case						       =				MBartTokenizer

				_snake_case						       =				[]
				_snake_case						       =				[]

				def __init__(     self							,      a_=None							,      a_=None							,      a_="<s>"							,      a_="</s>"							,      a_="</s>"							,      a_="<s>"							,      a_="<unk>"							,      a_="<pad>"							,      a_="<mask>"							,      a_=None							,      a_=None							,      a_=None							,      **a_							,      )    ->  List[Any]:
					lowercase						:		Optional[int]   					=		AddedToken(SCREAMING_SNAKE_CASE_							,      lstrip=SCREAMING_SNAKE_CASE_							,      rstrip=SCREAMING_SNAKE_CASE_							) if isinstance(SCREAMING_SNAKE_CASE_							,      SCREAMING_SNAKE_CASE_							) else mask_token

					super().__init__(
					    vocab_file=SCREAMING_SNAKE_CASE_							,      tokenizer_file=SCREAMING_SNAKE_CASE_							,      bos_token=SCREAMING_SNAKE_CASE_							,      eos_token=SCREAMING_SNAKE_CASE_							,      sep_token=SCREAMING_SNAKE_CASE_							,      cls_token=SCREAMING_SNAKE_CASE_							,      unk_token=SCREAMING_SNAKE_CASE_							,      pad_token=SCREAMING_SNAKE_CASE_							,      mask_token=SCREAMING_SNAKE_CASE_							,      src_lang=SCREAMING_SNAKE_CASE_							,      tgt_lang=SCREAMING_SNAKE_CASE_							,      additional_special_tokens=SCREAMING_SNAKE_CASE_							,      **SCREAMING_SNAKE_CASE_							,      )

					lowercase						:		Dict   					=		vocab_file
					lowercase						:		Optional[int]   					=		False if not self.vocab_file else True

					lowercase						:		List[Any]   					=		FAIRSEQ_LANGUAGE_CODES.copy()

					if additional_special_tokens is not None:
						# Only add those special tokens if they are not already there.
						_additional_special_tokens.extend(
						    [t for t in additional_special_tokens if t not in _additional_special_tokens]							)

					self.add_special_tokens({"additional_special_tokens": _additional_special_tokens}							)
					lowercase						:		Optional[Any]   					=		{
					    lang_code: self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_							) for lang_code in FAIRSEQ_LANGUAGE_CODES
					}

					lowercase						:		str   					=		src_lang if src_lang is not None else "en_XX"
					lowercase						:		Union[str, Any]   					=		self.convert_tokens_to_ids(self._src_lang							)
					lowercase						:		Optional[int]   					=		tgt_lang
					self.set_src_lang_special_tokens(self._src_lang							)

				@property
				def 	a__		(     self							)    ->  str:
					return self._src_lang

				@src_lang.setter
				def 	a__		(     self							,      a_							)    ->  None:
					lowercase						:		int   					=		new_src_lang
					self.set_src_lang_special_tokens(self._src_lang							)

				def 	a__		(     self							,      a_							,      a_ = None							)    ->  List[int]:


					if token_ids_a is None:
						return self.prefix_tokens + token_ids_a + self.suffix_tokens
					# We don't expect to process pairs, but leave the pair logic for API consistency
					return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens

				def 	a__		(     self							,      a_							,      a_ = None							)    ->  List[int]:
					lowercase						:		List[str]   					=		[self.sep_token_id]
					lowercase						:		Union[str, Any]   					=		[self.cls_token_id]

					if token_ids_a is None:
						return len(cls + token_ids_a + sep							) * [0]
					return len(cls + token_ids_a + sep + sep + token_ids_a + sep							) * [0]

				def 	a__		(     self							,      a_							,      a_							,      a_							,      a_							,      **a_							)    ->  Tuple:


					if src_lang is None or tgt_lang is None:
						raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"							)
					lowercase						:		str   					=		src_lang
					lowercase						:		List[str]   					=		self(SCREAMING_SNAKE_CASE_							,      add_special_tokens=SCREAMING_SNAKE_CASE_							,      return_tensors=SCREAMING_SNAKE_CASE_							,      **SCREAMING_SNAKE_CASE_							)
					lowercase						:		Tuple   					=		self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_							)
					lowercase						:		Optional[int]   					=		tgt_lang_id
					return inputs

				def 	a__		(     self							,      a_							,      a_ = "en_XX"							,      a_ = None							,      a_ = "ro_RO"							,      **a_							,      )    ->  BatchEncoding:
					lowercase						:		Tuple   					=		src_lang
					lowercase						:		Optional[Any]   					=		tgt_lang
					return super().prepare_seqaseq_batch(SCREAMING_SNAKE_CASE_							,      SCREAMING_SNAKE_CASE_							,      **SCREAMING_SNAKE_CASE_							)

				def 	a__		(     self							)    ->  Optional[Any]:
					return self.set_src_lang_special_tokens(self.src_lang							)

				def 	a__		(     self							)    ->  int:
					return self.set_tgt_lang_special_tokens(self.tgt_lang							)

				def 	a__		(     self							,      a_							)    ->  None:
					lowercase						:		Dict   					=		self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_							)
					lowercase						:		str   					=		[]
					lowercase						:		Tuple   					=		[self.eos_token_id, self.cur_lang_code]

					lowercase						:		str   					=		self.convert_ids_to_tokens(self.prefix_tokens							)
					lowercase						:		str   					=		self.convert_ids_to_tokens(self.suffix_tokens							)

					lowercase						:		List[str]   					=		processors.TemplateProcessing(
					    single=prefix_tokens_str + ["$A"] + suffix_tokens_str							,      pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str							,      special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str							,      self.prefix_tokens + self.suffix_tokens							)							)							,      )

				def 	a__		(     self							,      a_							)    ->  None:
					lowercase						:		Tuple   					=		self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_							)
					lowercase						:		Optional[int]   					=		[]
					lowercase						:		int   					=		[self.eos_token_id, self.cur_lang_code]

					lowercase						:		Optional[Any]   					=		self.convert_ids_to_tokens(self.prefix_tokens							)
					lowercase						:		Any   					=		self.convert_ids_to_tokens(self.suffix_tokens							)

					lowercase						:		str   					=		processors.TemplateProcessing(
					    single=prefix_tokens_str + ["$A"] + suffix_tokens_str							,      pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str							,      special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str							,      self.prefix_tokens + self.suffix_tokens							)							)							,      )


				def 	a__		(     self							,      a_							,      a_ = None							)    ->  Tuple[str]:


					if not self.can_save_slow_tokenizer:
						raise ValueError(
						    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
						    "tokenizer."							)

					if not os.path.isdir(SCREAMING_SNAKE_CASE_							):
						logger.error(F'''Vocabulary path ({save_directory}) should be a directory.'''							)
						return
					lowercase						:		str   					=		os.path.join(
					    SCREAMING_SNAKE_CASE_							,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]							)

					if os.path.abspath(self.vocab_file							) != os.path.abspath(SCREAMING_SNAKE_CASE_							):
						copyfile(self.vocab_file							,      SCREAMING_SNAKE_CASE_							)

					return (out_vocab_file,)




"""simple docstring"""






import warnings

from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor


UpperCAmelCase        =				logging.get_logger(__name__)



class 			lowercase					( lowercase__		):






			def __init__(self  :	str      ,*SCREAMING_SNAKE_CASE_  :	Any      ,**SCREAMING_SNAKE_CASE_  :	Optional[int]			)       ->	None:





				"""simple docstring"""


				warnings.warn(
				    '''The class PerceiverFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
				    ''' Please use PerceiverImageProcessor instead.'''      ,SCREAMING_SNAKE_CASE_      ,)
				super().__init__(*SCREAMING_SNAKE_CASE_      ,**SCREAMING_SNAKE_CASE_			)


